code: def inputs_all_ready(inputs, supported_ndim=(2, 4)):
      """Checks if input arrays are supported for an iDeep primitive.
  
      Before calling an iDeep primitive (e.g., ``ideep4py.linear.Forward``), you
      need to make sure that all input arrays are ready for the primitive by
      calling this function.
      Information to be checked includes array types, dimesions and data types.
      The function checks ``inputs`` info and ``supported_ndim``.
  
      Inputs to be tested can be any of ``Variable``, ``numpy.ndarray`` or
      ``ideep4py.mdarray``. However, all inputs to iDeep primitives must be
      ``ideep4py.mdarray``. Callers of iDeep primitives are responsible of
      converting all inputs to ``ideep4py.mdarray``.
  
      Args:
          inputs (sequence of arrays or variables):
              Inputs to be checked.
          supported_ndim (tuple of ints):
              Supported ndim values for the iDeep primitive.
  
      Returns:
          bool: ``True`` if all conditions meet.
  
      """
  
      def _is_supported_array_type(a):
          return isinstance(a, ideep.mdarray) or ideep.check_type([a])
  
      if not is_ideep_available():
          return False
  
      inputs = [
          x.data if isinstance(x, chainer.variable.Variable) else x
          for x in inputs
      ]
  
      return ideep.check_ndim(inputs, supported_ndim) and all(
          [_is_supported_array_type(a) for a in inputs]
      )
  
file_path: chainer/chainer/backends/intel64.py
imports: from __future__ import absolute_import
  import numpy
  import chainer
  from chainer import _backend
  from chainer.backends import _cpu
  from chainer.configuration import config
label_desc: Use image node_id 4 for calling a global function with example usage: inputs_all_ready(inputs, supported_ndim) and returns: unknown, unknown, False